Systems and methods for managing a highly available and scalable distributed database in a cloud computing environment

ABSTRACT

Systems and methods for managing a highly available distributed database comprising: a memory storing instructions; and one or more processors configured to execute the instructions to: determine that a source node, in a distributed database comprising the source node and one or more replica nodes, is not available; select a most-updated replica node from the one or more replica nodes; switch a role of the most-updated replica node to source; update a data store to label the source node as unavailable and the selected replica node as being a promoted source node; send a notification to a user device to update a database topology based on the updated data store; determine whether the user device has updated the database topology; and upon determining the user device has not updated the database topology, continue to send the notification to the user device until the user device has updated the database topology.

TECHNICAL FIELD

The present disclosure generally relates to computerized methods andsystems for building and maintaining a highly available and scalabledistributed database in a cloud computing environment. In particular,embodiments of the present disclosure relate to inventive andunconventional systems that maximize uptime, minimize error fromprolonged usage, and minimize failover time of databases by utilizing adata store to monitor the source of truth and notify the user device ofany changes.

BACKGROUND

Certain systems require databases which are always available. Theavailability of a database is measured by the percentage of healthy timein its lifetime. Generally, highly available databases are those thatare available 99.999% of the time or more. That is, they are down forfewer than 5.26 minutes per year. One method for achieving highavailability in a database is to create a distributed database. This isa database where data are stored in multiple nodes in differentlocations. A plurality of database nodes is called a cluster. In mostcases, a cluster consists of one source which serves write requests, andone or more replicas to serve read requests.

The idea behind distributed databases is that, should one node fail,there are others with the same data ready to take its place. Therefore,the database as a whole does not have to remain unavailable until thefailed node comes back online. When a node fails, a distributed databasewill usually select another node to take its place and the period duringwhich this occurs is called failover. Different systems have differentfailover times, but most still take minutes, which could be disastrousfor certain businesses. Further, there is currently no standalonesolution which can manage the distributed database and reduce failovertime in a cost-effective way. Indeed, current solutions solve problemswith availability by adding nodes to the distributed database, which ishighly inefficient and costly.

Therefore, there is a need for systems and methods for managing a highlyavailable and scalable distributed database in a cloud computingenvironment which reduce failover time to seconds and provide astandalone solution, with minimal redundancy for cost-efficiency. Suchsystems and methods would minimize failover time, lower the failurerate, and achieve greater uptime as a whole, providing businesses with acost-effective solution which minimizes interruptions due to failures.

SUMMARY

One aspect of the present disclosure is directed to acomputer-implemented system for managing a highly available distributeddatabase in a cloud computing environment. The system may comprise amemory storing instructions; and one or more processors configured toexecute the instructions to: determine that a source node, in adistributed database comprising the source node and one or more replicanodes, is not available; select a most-updated replica node from the oneor more replica nodes; switch a role of the most-updated replica nodefrom replica to source; update a data store to label the source node asunavailable and the selected replica node as being a promoted sourcenode; send a notification to a user device connected to the distributeddatabase to update a database topology log based on the updated datastore; determine whether the user device has updated the databasetopology log; and upon determining the user device has not updated thedatabase topology log, continue to send the notification to the userdevice until the user device has updated the database topology log.

Yet another aspect of the present disclosure is directed to acomputer-implemented method for managing a highly available distributeddatabase in a cloud computing environment. The method may comprise:determining that a source node, in a distributed database comprising thesource node and one or more replica nodes, is not available; selecting amost-updated replica node from the one or more replica nodes; switchinga role of the most-updated replica node from replica to source; updatinga data store to label the source node as unavailable and the selectedreplica node as being a promoted source node; sending a notification toa user device connected to the distributed database to update a databasetopology log based on the updated data store; determining whether theuser device has updated the database topology log; and upon determiningthe user device has not updated the database topology log, continuing tosend the notification to the user device until the user device hasupdated the database topology log.

Still further, another aspect of the present disclosure is directed to acomputer-implemented system for managing a highly available distributeddatabase in a cloud computing environment. The system may comprise: amemory storing instructions; and one or more processors configured toexecute the instructions to: determine that a source node, in adistributed database existing in a cloud computing environmentcomprising the source node and one or more replica nodes, is notavailable; select a most-updated replica node from the one or morereplica nodes; switch a role of the most-updated replica node fromreplica to source; update a data store to label the source node asunavailable and the selected replica node as being a promoted sourcenode; send a notification to a user device connected to the distributeddatabase to update a database topology log based on the updated datastore; determine whether the user device has updated the databasetopology log by checking the data store from a confirmation from theuser device; upon determining the user device has not updated thedatabase topology log, continue to send the notification to the userdevice until the user device has updated the database topology; and upondetermining the user device has updated the database topology log,terminating the previous connection with the user device.

Other systems, methods, and computer-readable media are also discussedherein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a schematic block diagram illustrating an exemplaryembodiment of a network comprising computerized systems forcommunications enabling shipping, transportation, and logisticsoperations, consistent with the disclosed embodiments.

FIG. 1B depicts a sample Search Result Page (SRP) that includes one ormore search results satisfying a search request along with interactiveuser interface elements, consistent with the disclosed embodiments.

FIG. 1C depicts a sample Single Display Page (SDP) that includes aproduct and information about the product along with interactive userinterface elements, consistent with the disclosed embodiments.

FIG. 1D depicts a sample Cart page that includes items in a virtualshopping cart along with interactive user interface elements, consistentwith the disclosed embodiments.

FIG. 1E depicts a sample Order page that includes items from the virtualshopping cart along with information regarding purchase and shipping,along with interactive user interface elements, consistent with thedisclosed embodiments.

FIG. 2 is a diagrammatic illustration of an exemplary fulfillment centerconfigured to utilize disclosed computerized systems, consistent withthe disclosed embodiments.

FIG. 3 is a schematic block diagram illustrating an exemplary embodimentof a cloud environment comprising a distributed database and a systemfor managing the distributed database, consistent with the disclosedembodiments.

FIG. 4A is a flowchart of an exemplary computerized method for replacinga source node with a replica node following a failure of the sourcenode, consistent with the disclosed embodiments.

FIG. 4B is a flowchart of an exemplary computerized method for replacinga replica node following a failure of the replica node, consistent withthe disclosed embodiments.

FIG. 5 is a flowchart of an exemplary computerized method for replacinga connection from a user device to a database after a change in thetopology of the database, consistent with the disclosed embodiments.

FIG. 6 is a flowchart of an exemplary computerized method for ensuringthe database topology is consistent with a data store, consistent withthe disclosed embodiments.

DETAILED DESCRIPTION

The following detailed description refers to the accompanying drawings.Wherever possible, the same reference numbers are used in the drawingsand the following description to refer to the same or similar parts.While several illustrative embodiments are described herein,modifications, adaptations and other implementations are possible. Forexample, substitutions, additions, or modifications may be made to thecomponents and steps illustrated in the drawings, and the illustrativemethods described herein may be modified by substituting, reordering,removing, or adding steps to the disclosed methods. Accordingly, thefollowing detailed description is not limited to the disclosedembodiments and examples. Instead, the proper scope of the invention isdefined by the appended claims.

Embodiments of the present disclosure are directed to computerizedmethods and systems that manage a highly available and scalabledistributed database, where constant uptime and minimal error rate aredesired.

Referring to FIG. 1A, a schematic block diagram 100 illustrating anexemplary embodiment of a system comprising computerized systems forcommunications enabling shipping, transportation, and logisticsoperations is shown. As illustrated in FIG. 1A, system 100 may include avariety of systems, each of which may be connected to one another viaone or more networks. The systems may also be connected to one anothervia a direct connection, for example, using a cable. The depictedsystems include a shipment authority technology (SAT) system 101, anexternal front end system 103, an internal front end system 105, atransportation system 107, mobile devices 107A, 107B, and 107C, sellerportal 109, shipment and order tracking (SOT) system 111, fulfillmentoptimization (FO) system 113, fulfillment messaging gateway (FMG) 115,supply chain management (SCM) system 117, warehouse management system119, mobile devices 119A, 119B, and 119C (depicted as being inside offulfillment center (FC) 200), 3rd party fulfillment systems 121A, 121B,and 121C, fulfillment center authorization system (FC Auth) 123, andlabor management system (LMS) 125.

SAT system 101, in some embodiments, may be implemented as a computersystem that monitors order status and delivery status. For example, SATsystem 101 may determine whether an order is past its Promised DeliveryDate (PDD) and may take appropriate action, including initiating a neworder, reshipping the items in the non-delivered order, canceling thenon-delivered order, initiating contact with the ordering customer, orthe like. SAT system 101 may also monitor other data, including output(such as a number of packages shipped during a particular time period)and input (such as the number of empty cardboard boxes received for usein shipping). SAT system 101 may also act as a gateway between differentdevices in system 100, enabling communication (e.g., usingstore-and-forward or other techniques) between devices such as externalfront end system 103 and FO system 113.

External front end system 103, in some embodiments, may be implementedas a computer system that enables external users to interact with one ormore systems in system 100. For example, in embodiments where system 100enables the presentation of systems to enable users to place an orderfor an item, external front end system 103 may be implemented as a webserver that receives search requests, presents item pages, and solicitspayment information. For example, external front end system 103 may beimplemented as a computer or computers running software such as theApache HTTP Server, Microsoft Internet Information Services (IIS),NGINX, or the like. In other embodiments, external front end system 103may run custom web server software designed to receive and processrequests from external devices (e.g., mobile device 102A or computer102B), acquire information from databases and other data stores based onthose requests, and provide responses to the received requests based onacquired information.

In some embodiments, external front end system 103 may include one ormore of a web caching system, a database, a search system, or a paymentsystem. In one aspect, external front end system 103 may comprise one ormore of these systems, while in another aspect, external front endsystem 103 may comprise interfaces (e.g., server-to-server,database-to-database, or other network connections) connected to one ormore of these systems.

An illustrative set of steps, illustrated by FIGS. 1B, 1C, 1D, and 1E,will help to describe some operations of external front end system 103.External front end system 103 may receive information from systems ordevices in system 100 for presentation and/or display. For example,external front end system 103 may host or provide one or more web pages,including a Search Result Page (SRP) (e.g., FIG. 1B), a Single DetailPage (SDP) (e.g., FIG. 1C), a Cart page (e.g., FIG. 1D), or an Orderpage (e.g., FIG. 1E). A user device (e.g., using mobile device 102A orcomputer 102B) may navigate to external front end system 103 and requesta search by entering information into a search box. External front endsystem 103 may request information from one or more systems in system100. For example, external front end system 103 may request informationfrom FO System 113 that satisfies the search request. External front endsystem 103 may also request and receive (from FO System 113) a PromisedDelivery Date or “PDD” for each product included in the search results.The PDD, in some embodiments, may represent an estimate of when apackage containing the product will arrive at the user's desiredlocation or a date by which the product is promised to be delivered atthe user's desired location if ordered within a particular period oftime, for example, by the end of the day (11:59 PM). (PDD is discussedfurther below with respect to FO System 113.)

External front end system 103 may prepare an SRP (e.g., FIG. 1B) basedon the information. The SRP may include information that satisfies thesearch request. For example, this may include pictures of products thatsatisfy the search request. The SRP may also include respective pricesfor each product, or information relating to enhanced delivery optionsfor each product, PDD, weight, size, offers, discounts, or the like.External front end system 103 may send the SRP to the requesting userdevice (e.g., via a network).

A user device may then select a product from the SRP, e.g., by clickingor tapping a user interface, or using another input device, to select aproduct represented on the SRP. The user device may formulate a requestfor information on the selected product and send it to external frontend system 103. In response, external front end system 103 may requestinformation related to the selected product. For example, theinformation may include additional information beyond that presented fora product on the respective SRP. This could include, for example, shelflife, country of origin, weight, size, number of items in package,handling instructions, or other information about the product. Theinformation could also include recommendations for similar products(based on, for example, big data and/or machine learning analysis ofcustomers who bought this product and at least one other product),answers to frequently asked questions, reviews from customers,manufacturer information, pictures, or the like.

External front end system 103 may prepare an SDP (Single Detail Page)(e.g., FIG. 1C) based on the received product information. The SDP mayalso include other interactive elements such as a “Buy Now” button, a“Add to Cart” button, a quantity field, a picture of the item, or thelike. The SDP may further include a list of sellers that offer theproduct. The list may be ordered based on the price each seller offerssuch that the seller that offers to sell the product at the lowest pricemay be listed at the top. The list may also be ordered based on theseller ranking such that the highest ranked seller may be listed at thetop. The seller ranking may be formulated based on multiple factors,including, for example, the seller's past track record of meeting apromised PDD. External front end system 103 may deliver the SDP to therequesting user device (e.g., via a network).

The requesting user device may receive the SDP which lists the productinformation. Upon receiving the SDP, the user device may then interactwith the SDP. For example, a user of the requesting user device mayclick or otherwise interact with a “Place in Cart” button on the SDP.This adds the product to a shopping cart associated with the user. Theuser device may transmit this request to add the product to the shoppingcart to external front end system 103.

External front end system 103 may generate a Cart page (e.g., FIG. 1D).The Cart page, in some embodiments, lists the products that the user hasadded to a virtual “shopping cart.” A user device may request the Cartpage by clicking on or otherwise interacting with an icon on the SRP,SDP, or other pages. The Cart page may, in some embodiments, list allproducts that the user has added to the shopping cart, as well asinformation about the products in the cart such as a quantity of eachproduct, a price for each product per item, a price for each productbased on an associated quantity, information regarding PDD, a deliverymethod, a shipping cost, user interface elements for modifying theproducts in the shopping cart (e.g., deletion or modification of aquantity), options for ordering other product or setting up periodicdelivery of products, options for setting up interest payments, userinterface elements for proceeding to purchase, or the like. A user at auser device may click on or otherwise interact with a user interfaceelement (e.g., a button that reads “Buy Now”) to initiate the purchaseof the product in the shopping cart. Upon doing so, the user device maytransmit this request to initiate the purchase to external front endsystem 103.

External front end system 103 may generate an Order page (e.g., FIG. 1E)in response to receiving the request to initiate a purchase. The Orderpage, in some embodiments, re-lists the items from the shopping cart andrequests input of payment and shipping information. For example, theOrder page may include a section requesting information about thepurchaser of the items in the shopping cart (e.g., name, address, e-mailaddress, phone number), information about the recipient (e.g., name,address, phone number, delivery information), shipping information(e.g., speed/method of delivery and/or pickup), payment information(e.g., credit card, bank transfer, check, stored credit), user interfaceelements to request a cash receipt (e.g., for tax purposes), or thelike. External front end system 103 may send the Order page to the userdevice.

The user device may enter information on the Order page and click orotherwise interact with a user interface element that sends theinformation to external front end system 103. From there, external frontend system 103 may send the information to different systems in system100 to enable the creation and processing of a new order with theproducts in the shopping cart.

In some embodiments, external front end system 103 may be furtherconfigured to enable sellers to transmit and receive informationrelating to orders.

Internal front end system 105, in some embodiments, may be implementedas a computer system that enables internal users (e.g., employees of anorganization that owns, operates, or leases system 100) to interact withone or more systems in system 100. For example, in embodiments wheresystem 100 enables the presentation of systems to enable users to placean order for an item, internal front end system 105 may be implementedas a web server that enables internal users to view diagnostic andstatistical information about orders, modify item information, or reviewstatistics relating to orders. For example, internal front end system105 may be implemented as a computer or computers running software suchas the Apache HTTP Server, Microsoft Internet Information Services(IIS), NGINX, or the like. In other embodiments, internal front endsystem 105 may run custom web server software designed to receive andprocess requests from systems or devices depicted in system 100 (as wellas other devices not depicted), acquire information from databases andother data stores based on those requests, and provide responses to thereceived requests based on acquired information.

In some embodiments, internal front end system 105 may include one ormore of a web caching system, a database, a search system, a paymentsystem, an analytics system, an order monitoring system, or the like. Inone aspect, internal front end system 105 may comprise one or more ofthese systems, while in another aspect, internal front end system 105may comprise interfaces (e.g., server-to-server, database-to-database,or other network connections) connected to one or more of these systems.

Transportation system 107, in some embodiments, may be implemented as acomputer system that enables communication between systems or devices insystem 100 and mobile devices 107A-107C. Transportation system 107, insome embodiments, may receive information from one or more mobiledevices 107A-107C (e.g., mobile phones, smart phones, PDAs, or thelike). For example, in some embodiments, mobile devices 107A-107C maycomprise devices operated by delivery workers. The delivery workers, whomay be permanent, temporary, or shift employees, may utilize mobiledevices 107A-107C to effect delivery of packages containing the productsordered by users. For example, to deliver a package, the delivery workermay receive a notification on a mobile device indicating which packageto deliver and where to deliver it. Upon arriving at the deliverylocation, the delivery worker may locate the package (e.g., in the backof a truck or in a crate of packages), scan or otherwise capture dataassociated with an identifier on the package (e.g., a barcode, an image,a text string, an RFID tag, or the like) using the mobile device, anddeliver the package (e.g., by leaving it at a front door, leaving itwith a security guard, handing it to the recipient, or the like). Insome embodiments, the delivery worker may capture photo(s) of thepackage and/or may obtain a signature using the mobile device. Themobile device may send information to transportation system 107including information about the delivery, including, for example, time,date, GPS location, photo(s), an identifier associated with the deliveryworker, an identifier associated with the mobile device, or the like.Transportation system 107 may store this information in a database (notpictured) for access by other systems in system 100. Transportationsystem 107 may, in some embodiments, use this information to prepare andsend tracking data to other systems indicating the location of aparticular package.

In some embodiments, certain users may use one kind of mobile device(e.g., permanent workers may use a specialized PDA with custom hardwaresuch as a barcode scanner, stylus, and other devices) while other usersmay use other kinds of mobile devices (e.g., temporary or shift workersmay utilize off-the-shelf mobile phones and/or smartphones).

In some embodiments, transportation system 107 may associate a user witheach device. For example, transportation system 107 may store anassociation between a user (represented by, e.g., a user identifier, anemployee identifier, or a phone number) and a mobile device (representedby, e.g., an International Mobile Equipment Identity (IMEI), anInternational Mobile Subscription Identifier (IMSI), a phone number, aUniversal Unique Identifier (UUID), or a Globally Unique Identifier(GUID)). Transportation system 107 may use this association inconjunction with data received on deliveries to analyze data stored inthe database in order to determine, among other things, a location ofthe worker, an efficiency of the worker, or a speed of the worker.

Seller portal 109, in some embodiments, may be implemented as a computersystem that enables sellers or other external entities to electronicallycommunicate with one or more systems in system 100. For example, aseller may utilize a computer system (not pictured) to upload or provideproduct information, order information, contact information, or thelike, for products that the seller wishes to sell through system 100using seller portal 109.

Shipment and order tracking system 111, in some embodiments, may beimplemented as a computer system that receives, stores, and forwardsinformation regarding the location of packages containing productsordered by customers (e.g., by a user using devices 102A-102B). In someembodiments, shipment and order tracking system 111 may request or storeinformation from web servers (not pictured) operated by shippingcompanies that deliver packages containing products ordered bycustomers.

In some embodiments, shipment and order tracking system 111 may requestand store information from systems depicted in system 100. For example,shipment and order tracking system 111 may request information fromtransportation system 107. As discussed above, transportation system 107may receive information from one or more mobile devices 107A-107C (e.g.,mobile phones, smart phones, PDAs, or the like) that are associated withone or more of a user (e.g., a delivery worker) or a vehicle (e.g., adelivery truck). In some embodiments, shipment and order tracking system111 may also request information from warehouse management system (WMS)119 to determine the location of individual products inside of afulfillment center (e.g., fulfillment center 200). Shipment and ordertracking system 111 may request data from one or more of transportationsystem 107 or WMS 119, process it, and present it to a device (e.g.,user devices 102A and 102B) upon request.

Fulfillment optimization (FO) system 113, in some embodiments, may beimplemented as a computer system that stores information for customerorders from other systems (e.g., external front end system 103 and/orshipment and order tracking system 111). FO system 113 may also storeinformation describing where particular items are held or stored. Forexample, certain items may be stored only in one fulfillment center,while certain other items may be stored in multiple fulfillment centers.In still other embodiments, certain fulfilment centers may be designedto store only a particular set of items (e.g., fresh produce or frozenproducts). FO system 113 stores this information as well as associatedinformation (e.g., quantity, size, date of receipt, expiration date,etc.).

FO system 113 may also calculate a corresponding PDD (promised deliverydate) for each product. The PDD, in some embodiments, may be based onone or more factors. For example, FO system 113 may calculate a PDD fora product based on a past demand for a product (e.g., how many timesthat product was ordered during a period of time), an expected demandfor a product (e.g., how many customers are forecast to order theproduct during an upcoming period of time), a network-wide past demandindicating how many products were ordered during a period of time, anetwork-wide expected demand indicating how many products are expectedto be ordered during an upcoming period of time, one or more counts ofthe product stored in each fulfillment center 200, which fulfillmentcenter stores each product, expected or current orders for that product,or the like.

In some embodiments, FO system 113 may determine a PDD for each producton a periodic basis (e.g., hourly) and store it in a database forretrieval or sending to other systems (e.g., external front end system103, SAT system 101, shipment and order tracking system 111). In otherembodiments, FO system 113 may receive electronic requests from one ormore systems (e.g., external front end system 103, SAT system 101,shipment and order tracking system 111) and calculate the PDD on demand.

Fulfilment messaging gateway (FMG) 115, in some embodiments, may beimplemented as a computer system that receives a request or response inone format or protocol from one or more systems in system 100, such asFO system 113, converts it to another format or protocol, and forward itin the converted format or protocol to other systems, such as WMS 119 or3rd party fulfillment systems 121A, 121B, or 121C, and vice versa.

Supply chain management (SCM) system 117, in some embodiments, may beimplemented as a computer system that performs forecasting functions.For example, SCM system 117 may forecast a level of demand for aparticular product based on, for example, based on a past demand forproducts, an expected demand for a product, a network-wide past demand,a network-wide expected demand, a count products stored in eachfulfillment center 200, expected or current orders for each product, orthe like. In response to this forecasted level and the amount of eachproduct across all fulfillment centers, SCM system 117 may generate oneor more purchase orders to purchase and stock a sufficient quantity tosatisfy the forecasted demand for a particular product.

Warehouse management system (WMS) 119, in some embodiments, may beimplemented as a computer system that monitors workflow. For example,WMS 119 may receive event data from individual devices (e.g., devices107A-107C or 119A-119C) indicating discrete events. For example, WMS 119may receive event data indicating the use of one of these devices toscan a package. As discussed below with respect to fulfillment center200 and FIG. 2, during the fulfillment process, a package identifier(e.g., a barcode or RFID tag data) may be scanned or read by machines atparticular stages (e.g., automated or handheld barcode scanners, RFIDreaders, high-speed cameras, devices such as tablet 119A, mobiledevice/PDA 1198, computer 119C, or the like). WMS 119 may store eachevent indicating a scan or a read of a package identifier in acorresponding database (not pictured) along with the package identifier,a time, date, location, user identifier, or other information, and mayprovide this information to other systems (e.g., shipment and ordertracking system 111).

WMS 119, in some embodiments, may store information associating one ormore devices (e.g., devices 107A-107C or 119A-119C) with one or moreusers associated with system 100. For example, in some situations, auser (such as a part- or full-time employee) may be associated with amobile device in that the user owns the mobile device (e.g., the mobiledevice is a smartphone). In other situations, a user may be associatedwith a mobile device in that the user is temporarily in custody of themobile device (e.g., the user checked the mobile device out at the startof the day, will use it during the day, and will return it at the end ofthe day).

WMS 119, in some embodiments, may maintain a work log for each userassociated with system 100. For example, WMS 119 may store informationassociated with each employee, including any assigned processes (e.g.,unloading trucks, picking items from a pick zone, rebin wall work,packing items), a user identifier, a location (e.g., a floor or zone ina fulfillment center 200), a number of units moved through the system bythe employee (e.g., number of items picked, number of items packed), anidentifier associated with a device (e.g., devices 119A-119C), or thelike. In some embodiments, WMS 119 may receive check-in and check-outinformation from a timekeeping system, such as a timekeeping systemoperated on a device 119A-119C.

3rd party fulfillment (3PL) systems 121A-121C, in some embodiments,represent computer systems associated with third-party providers oflogistics and products. For example, while some products are stored infulfillment center 200 (as discussed below with respect to FIG. 2),other products may be stored off-site, may be produced on demand, or maybe otherwise unavailable for storage in fulfillment center 200. 3PLsystems 121A-121C may be configured to receive orders from FO system 113(e.g., through FMG 115) and may provide products and/or services (e.g.,delivery or installation) to customers directly. In some embodiments,one or more of 3PL systems 121A-121C may be part of system 100, while inother embodiments, one or more of 3PL systems 121A-121C may be outsideof system 100 (e.g., owned or operated by a third party provider).

Fulfillment Center Auth system (FC Auth) 123, in some embodiments, maybe implemented as a computer system with a variety of functions. Forexample, in some embodiments, FC Auth 123 may act as a single-sign on(SSO) service for one or more other systems in system 100. For example,FC Auth 123 may enable a user to log in via internal front end system105, determine that the user has similar privileges to access resourcesat shipment and order tracking system 111, and enable the user to accessthose privileges without requiring a second log in process. FC Auth 123,in other embodiments, may enable users (e.g., employees) to associatethemselves with a particular task. For example, some employees may nothave an electronic device (such as devices 119A-119C) and may insteadmove from task to task, and zone to zone, within a fulfillment center200, during the course of a day. FC Auth 123 may be configured to enablethose employees to indicate what task they are performing and what zonethey are in at different times of day.

Labor management system (LMS) 125, in some embodiments, may beimplemented as a computer system that stores attendance and overtimeinformation for employees (including full-time and part-time employees).For example, LMS 125 may receive information from FC Auth 123, WMS 119,devices 119A-119C, transportation system 107, and/or devices 107A-107C.

The particular configuration depicted in FIG. 1A is an example only. Forexample, while FIG. 1A depicts FC Auth system 123 connected to FO system113, not all embodiments require this particular configuration. Indeed,in some embodiments, the systems in system 100 may be connected to oneanother through one or more public or private networks, including theInternet, an Intranet, a WAN (Wide-Area Network), a MAN(Metropolitan-Area Network), a wireless network compliant with the IEEE802.11a/b/g/n Standards, a leased line, or the like. In someembodiments, one or more of the systems in system 100 may be implementedas one or more virtual servers implemented at a data center, serverfarm, or the like.

FIG. 2 depicts a fulfillment center 200. Fulfillment center 200 is anexample of a physical location that stores items for shipping tocustomers when ordered. Fulfillment center (FC) 200 may be divided intomultiple zones, each of which are depicted in FIG. 2. These “zones,” insome embodiments, may be thought of as virtual divisions betweendifferent stages of a process of receiving items, storing the items,retrieving the items, and shipping the items. So while the “zones” aredepicted in FIG. 2, other divisions of zones are possible, and the zonesin FIG. 2 may be omitted, duplicated, or modified in some embodiments.

Inbound zone 203 represents an area of FC 200 where items are receivedfrom sellers who wish to sell products using system 100 from FIG. 1A.For example, a seller may deliver items 202A and 202B using truck 201.Item 202A may represent a single item large enough to occupy its ownshipping pallet, while item 202B may represent a set of items that arestacked together on the same pallet to save space.

A worker will receive the items in inbound zone 203 and may optionallycheck the items for damage and correctness using a computer system (notpictured). For example, the worker may use a computer system to comparethe quantity of items 202A and 202B to an ordered quantity of items. Ifthe quantity does not match, that worker may refuse one or more of items202A or 2026. If the quantity does match, the worker may move thoseitems (using, e.g., a dolly, a handtruck, a forklift, or manually) tobuffer zone 205. Buffer zone 205 may be a temporary storage area foritems that are not currently needed in the picking zone, for example,because there is a high enough quantity of that item in the picking zoneto satisfy forecasted demand. In some embodiments, forklifts 206 operateto move items around buffer zone 205 and between inbound zone 203 anddrop zone 207. If there is a need for items 202A or 202B in the pickingzone (e.g., because of forecasted demand), a forklift may move items202A or 202B to drop zone 207.

Drop zone 207 may be an area of FC 200 that stores items before they aremoved to picking zone 209. A worker assigned to the picking task (a“picker”) may approach items 202A and 202B in the picking zone, scan abarcode for the picking zone, and scan barcodes associated with items202A and 202B using a mobile device (e.g., device 119B). The picker maythen take the item to picking zone 209 (e.g., by placing it on a cart orcarrying it).

Picking zone 209 may be an area of FC 200 where items 208 are stored onstorage units 210. In some embodiments, storage units 210 may compriseone or more of physical shelving, bookshelves, boxes, totes,refrigerators, freezers, cold stores, or the like. In some embodiments,picking zone 209 may be organized into multiple floors. In someembodiments, workers or machines may move items into picking zone 209 inmultiple ways, including, for example, a forklift, an elevator, aconveyor belt, a cart, a handtruck, a dolly, an automated robot ordevice, or manually. For example, a picker may place items 202A and 202Bon a handtruck or cart in drop zone 207 and walk items 202A and 202B topicking zone 209.

A picker may receive an instruction to place (or “stow”) the items inparticular spots in picking zone 209, such as a particular space on astorage unit 210. For example, a picker may scan item 202A using amobile device (e.g., device 119B). The device may indicate where thepicker should stow item 202A, for example, using a system that indicatean aisle, shelf, and location. The device may then prompt the picker toscan a barcode at that location before stowing item 202A in thatlocation. The device may send (e.g., via a wireless network) data to acomputer system such as WMS 119 in FIG. 1A indicating that item 202A hasbeen stowed at the location by the user using device 1196.

Once a user places an order, a picker may receive an instruction ondevice 119B to retrieve one or more items 208 from storage unit 210. Thepicker may retrieve item 208, scan a barcode on item 208, and place iton transport mechanism 214. While transport mechanism 214 is representedas a slide, in some embodiments, transport mechanism may be implementedas one or more of a conveyor belt, an elevator, a cart, a forklift, ahandtruck, a dolly, a cart, or the like. Item 208 may then arrive atpacking zone 211.

Packing zone 211 may be an area of FC 200 where items are received frompicking zone 209 and packed into boxes or bags for eventual shipping tocustomers. In packing zone 211, a worker assigned to receiving items (a“rebin worker”) will receive item 208 from picking zone 209 anddetermine what order it corresponds to. For example, the rebin workermay use a device, such as computer 119C, to scan a barcode on item 208.Computer 119C may indicate visually which order item 208 is associatedwith. This may include, for example, a space or “cell” on a wall 216that corresponds to an order. Once the order is complete (e.g., becausethe cell contains all items for the order), the rebin worker mayindicate to a packing worker (or “packer”) that the order is complete.The packer may retrieve the items from the cell and place them in a boxor bag for shipping. The packer may then send the box or bag to a hubzone 213, e.g., via forklift, cart, dolly, handtruck, conveyor belt,manually, or otherwise.

Hub zone 213 may be an area of FC 200 that receives all boxes or bags(“packages”) from packing zone 211. Workers and/or machines in hub zone213 may retrieve package 218 and determine which portion of a deliveryarea each package is intended to go to, and route the package to anappropriate camp zone 215. For example, if the delivery area has twosmaller sub-areas, packages will go to one of two camp zones 215. Insome embodiments, a worker or machine may scan a package (e.g., usingone of devices 119A-119C) to determine its eventual destination. Routingthe package to camp zone 215 may comprise, for example, determining aportion of a geographical area that the package is destined for (e.g.,based on a postal code) and determining a camp zone 215 associated withthe portion of the geographical area.

Camp zone 215, in some embodiments, may comprise one or more buildings,one or more physical spaces, or one or more areas, where packages arereceived from hub zone 213 for sorting into routes and/or sub-routes. Insome embodiments, camp zone 215 is physically separate from FC 200 whilein other embodiments camp zone 215 may form a part of FC 200.

Workers and/or machines in camp zone 215 may determine which routeand/or sub route a package 220 should be associated with, for example,based on a comparison of the destination to an existing route and/orsub-route, a calculation of workload for each route and/or sub-route,the time of day, a shipping method, the cost to ship the package 220, aPDD associated with the items in package 220, or the like. In someembodiments, a worker or machine may scan a package (e.g., using one ofdevices 119A-119C) to determine its eventual destination. Once package220 is assigned to a particular route and/or sub route, a worker and/ormachine may move package 220 to be shipped. In exemplary FIG. 2, campzone 215 includes a truck 222, a car 226, and delivery workers 224A and224B. In some embodiments, truck 222 may be driven by delivery worker224A, where delivery worker 224A is a full-time employee that deliverspackages for FC 200 and truck 222 is owned, leased, or operated by thesame company that owns, leases, or operates FC 200. In some embodiments,car 226 may be driven by delivery worker 224B, where delivery worker224B is a “flex” or occasional worker that is delivering on an as-neededbasis (e.g., seasonally). Car 226 may be owned, leased, or operated bydelivery worker 224B.

FIG. 3 is a schematic block diagram illustrating an exemplary embodimentof a cloud environment 300 comprising a distributed database and asystem for managing the distributed database. Cloud environment 300 maycomprise a variety of computerized systems, each of which may beconnected to each other via one or more networks. In some embodiments,each of the elements depicted in FIG. 3 may represent a group ofsystems, individual systems in a network of systems, functional units ormodules inside a system, or any combination thereof. And in someembodiments, each of the elements may communicate with each other viaone or more public or private network connections including theInternet, an intranet, a WAN (Wide-Area Network), a MAN(Metropolitan-Area Network), a wireless network compliant with the IEEE802.11a/b/g/n Standards, a wired network, or the like. The individualsystems may also be located within one geographical location or begeographically dispersed.

In some embodiments, the depicted systems may include an orchestrator310, a distributed consistent store 320, a database cluster 330including a source node 331 and a plurality of replica nodes 332(depicted are two replica nodes 332 a and 332 b), a health checker 340,and a user device 350. While only two replica nodes 332 a and 332 b aredepicted in FIG. 3, the number is only exemplary and fewer or additionalreplica nodes may be implemented.

Each system depicted in FIG. 3 may take the form of a server,general-purpose computer, a mainframe computer, a special-purposecomputing device such as a graphical processing unit (GPU), laptop, orany combination of these computing devices. In other embodiments, eachsystem or a subset of the systems may be implemented as one or morefunctional units of a single system. Additionally or alternatively, eachsystem or a subset thereof may be a standalone system, or a part of asubsystem, which may be part of a larger system.

Orchestrator 310, in some embodiments, may be any computerized systemconfigured to manage the topology of database cluster 330. The topologyof a database cluster refers to the arrangement of the elements (i.e.,nodes) in a network of connected databases. For example, the topology ofdatabase cluster 330 may be described as three nodes, with a source nodewhich serves write queries (i.e., source node 331) and two replica nodeswhich serve read queries (i.e., replica nodes 332 a and 332 b). In someembodiments, orchestrator 310 may determine that source node 331 and/orone or more replica nodes 332 are not available. Upon thisdetermination, orchestrator 310 may trigger a failover method which mayreplace the failed nodes with healthy nodes and update consistent store320 with the new topology of database cluster 330. Orchestrator 310 maybe a relational database management system (RDBMS) such as, but notlimited to, Oracle Database, MySQL, Microsoft SQL Server, and IBM DB2.In some embodiments, orchestrator 310 may be distributed such thatshould one server endpoint of orchestrator 310 fail, one or moreendpoints remain to continue managing database cluster 330.

Distributed consistent store 320, in some embodiments, may be anycomputerized system configured to store information relating to thetopology of database cluster 330 and also configured to sendnotifications regarding the topology of database cluster 330 to userdevice 350. Consistent store 320 may be a relational database where datastored therein is organized in one or more data sets. For example,consistent store 320 may contain information labeling source node 331 asthe source node and replica nodes 332 a and 332 b as replica nodes.Additionally, consistent store 320 may contain information regarding thecurrent connections user device 350 maintains with database cluster 330,user device 350 data and statistics, and a last seen time correspondingto the last time either orchestrator 310, health checker 340, and/oruser device 350 interacted with consistent store 320. In someembodiments, consistent store 320 may be equipped to send a notificationto user device 350 to record the new database topology of databasecluster 330.

In other embodiments, consistent store 320 may be able to detect whetheruser device 350 has updated its database topology following thenotification. This detection may be the result of consistent store 320retrieving data from user device 350 and/or user device 350 sending dataof its current database topology to consistent store 320. Consistentstore 320 may be distributed such that one or more nodes store the sameor complementary data relating to the topology of database cluster 330.This may prevent data loss in the event of node failure. The nodes ofconsistent store 320 may all be configured to read and write, or thesetasks may be distributed among the plurality of nodes. Compared toconventional databases, separating the read and write functionalitiesinto dedicated nodes allows each functionality to take place withoutbeing intermingled with the other, thus lowering the risk of write orread errors.

Database cluster 330, in some embodiments, may be a computerized systemconfigured to collect, organize, and store various data. Databasecluster 330 may be a relational database where data stored therein isorganized in one or more data sets. Database cluster 330 may includedata such as that stored in or accessed by SAT system 101, externalfront end system 103, internal front end system 105, transportationsystem 107, SOT system 111, FO system 113, SCM system 117, warehousemanagement system 119, 3rd party fulfillment systems 121A, 121B, and121C, FC Auth 123, and/or LMS 125.

Database cluster 330 may include a source node 331 and one or morereplica nodes 332 a and 332 b. Source node 331 may be configured toprocess write requests sent by user device 350, while replica nodes 332a and 332 b may be configured to process read requests sent by userdevice 350. Contrary to conventional nodes that are configured to bothaccept new data for storage and make the data available for clientdevices (e.g., user device 350), source node 331 may be configuredsolely to collect and maintain the latest data set by accepting new datafrom user device 350. Each replica node 332 a/332 b may further beconfigured to store data identical to those stored in source node 331.For example, if source node 331 includes data sets 1-10 (i.e., a masterset), each replica node 332 may be configured to replicate and storedata sets 1-10. As discussed above, separating the read and writefunctionalities into dedicated nodes lowers the risk of write or readerrors. Each replica node 332 has the ability to be promoted to a sourcenode should source node 331 fail and orchestrator 310 trigger afailover.

Health checker 340, in some embodiments, may be any computerized systemconfigured to ensure the topology of database cluster 330 matches thetopology of database cluster 330 stored in consistent store 320 and tocheck the health of source node 331 and replica nodes 332 a/332 b. Forexample, health checker 340 may monitor consistent store 320 anddatabase cluster 330 in a specific time interval to ensure that both thetopology of database cluster 330 and the labeling in consistent store320 matches. If health checker 340 determines that these data do notmatch—this may occur, for example, if there is a network error betweenorchestrator 310 switching the role of one of replica nodes 332 a or 332b in database cluster 330 and updating consistent store 320—healthchecker 340 may update consistent store 320 itself, without goingthrough orchestrator 310, to reflect the current topology of databasecluster 330. Health checker 340 increases the resiliency of a systemwhich is expected to be available continuously as it reduces thepossibility of a rare error (e.g., network failure) impacting theperformance of the system.

User device 350, in some embodiments, may be any computerized systemconfigured to allow a user to read and/or write data in database cluster330. User device 350 may be one or more of mobile device 102A, computer1026, mobile devices 107A, 107B, and 107C, external front end system103, internal front end system 105, mobile devices 119A, 119B, and 119C,or any other system depicted in FIG. 1A.

In some embodiments, user device 350 may be configured to receivenotifications from consistent store 320, automatically update source andreplica endpoints based on the notification, and replace the connectionsto consistent store 320 using the updated endpoints. In otherembodiments, the update of the source and replica endpoints may takeplace only following user input. In yet other embodiments, user device350 may be configured to send a confirmation receipt to consistent store320 once user device 350 has updated its log of the topology of databasecluster 330 following a notification from consistent store 320. Userdevice 350 may be a personal computing device including, but not limitedto, a smartphone, a laptop or notebook computer, a tablet, amultifunctional watch, a pair of multifunctional glasses, any mobile orwearable device with computing ability, or any combination of thesecomputers and/or affiliated components.

FIG. 4A is a flowchart of an exemplary computerized method 400 forreplacing source node 331 with a replica node following a failure ofsource node 331. Method 400 may be performed in 1-10 seconds, asubstantial improvement from previous solutions. Method 400 may beimplemented utilizing data stored in any server that must service alarge number of queries such as, for example, SAT system 101, externalfront end system 103, internal front end system 105, transportationsystem 107, SOT system 111, FO system 113, SCM system 117, warehousemanagement system 119, 3rd party fulfillment systems 121A, 121B, and121C, FC Auth 123, and/or LMS 125. Such server may comprise networkedsystems such as those described above in FIG. 3. Method 400 is describedbelow with reference to the networked systems of FIG. 3, but any otherconfiguration of systems, subsystems, or modules may be used to performmethod 400.

At step 410, orchestrator 310 and/or health checker 340 may check theavailability of source node 331. Checking the availability of sourcenode 331 and/or one or more replica nodes 332 a and 332 b may beaccomplished by a detecting a number of failure scenarios, such as afailed source node, a failed source node and failed replica nodes, afailed source node and some failed replica nodes, an unreachable sourcenode, an unreachable source node with lagging replica nodes, not allreplica nodes are replicating the source node data, not all replicanodes are replicating the source node data or have failed, a failedco-source node (should the system have more than one source node), afailed co-source node and failed replica nodes, a failed replica nodewhich itself has replicas, a failed replica node which itself has onereplica which is failing to connect, a failed replica node which itselfhas one replica, a failed replica node which itself has one or morereplicas which have failed, a failed replica node which itself has oneor more replicas—some of which have failed, all replica nodes whichthemselves have one or more replicas have failed or are unable toconnect, an unreachable replica node which itself has one or morereplicas is unreachable, an unreachable replica node which itself hasone or more replicas which are lagging is unreachable.

The failure scenarios may be detected by attempting to reach and/oraccess source node 331 and/or one or more replica nodes 332 a and 332 b,determining one or more replica nodes is failing replication,determining source node 331 and/or one or more replica nodes 332 a and332 b are lagging, and other methods for detecting failure scenarios.

In other embodiments, orchestrator 310 and/or health checker 340 may usesynthetic monitoring to simulate an action or path that a user usinguser device 350 may take on each node in database cluster 330 to checkthe availability of source node 321 and/or one or more replica nodes.The actions or paths may then be continuously monitored at predeterminedintervals to test the availability of each node. Should the actions orpaths be completed successfully, orchestrator 310 and/or health checker340 may determine that the node is available. Further, depending on thescale and the desired availability of the system, the predeterminedintervals could range anywhere from milliseconds to hours. Other methodsfor checking the availability of the nodes include attempting to open aconnection to the nodes, executing a read query against the nodes,executing a non-cached write query against the nodes, executing aprewritten function or procedure that checks for the availability of thenodes, and/or any other method for checking the availability of adatabase.

At step 420, orchestrator 310 and/or health checker 340 may determinewhether source node 331 is available from the data collected at step410. Should source node 331 be available, method 400 may proceed to step422, where orchestrator 310 and/or health checker 340 may update a lastseen time in consistent store 320 and wait for a specific interval oftime before checking the availability of source node 331 once again.

However, if source node 331 is not available, method 400 may proceed tostep 430, where orchestrator 310 may select a most-updated replica nodefrom the one or more replica nodes 332. If health checker 340 determinedthat source node 331 is not available, health checker 340 may notifyorchestrator 310 that source node 331 is not available, also triggeringstep 430. The most-updated replica node may be, as its name wouldsuggest, the last replica node 332 a or 332 b to have been updated withthe data from source node 331 before it failed. Orchestrator 310 maystore an instance or list identifying the most-updated replica nodeand/or may pull data relating to the most-updated replica node from SATsystem 101, external front end system 103, internal front end system105, transportation system 107, SOT system 111, FO system 113, SCMsystem 117, warehouse management system 119, 3rd party fulfillmentsystems 121A, 121B, and 121C, FC Auth 123, and/or LMS 125.

At step 440, orchestrator 310 may check to see whether it has selected areplica node 332 before continuing to ensure the failover process iscarried out correctly. Should orchestrator 310 determine that no replicanode 332 has been selected, method 400 may proceed to step 442, whereorchestrator 310 may alert a system administrator (e.g., by sending atext message, email message, push notification, or othermessage/notification), exit method 400, and potentially begin method 400again at step 410 or step 430.

Alternatively, orchestrator 310 may determine that a replica node 332has indeed been selected and method 400 may proceed to step 450. For thepurpose of this illustration, we may assume that the most-updatedreplica node in this case was 332 a. At step 450, orchestrator 310 mayswitch the role of replica node 332 a from “replica” to “source,” alsoknown as source or master promotion, converting replica node 332 a intopromoted source node 332 a. This may take place by executing one or more“set” commands in SQL or a similar function in whichever language isbeing utilized. For example, orchestrator 310 may use a “set” command toset replica node 322 a as “writable.” Additionally or alternatively,orchestrator 310 may remove the role of source node 331 by using a “set”command to set source node 331 to be “read-only” or “super-read-only,”converting source node 331 into demoted source node 331.

At step 460, orchestrator 310 may update the labels in consistent store320 to reflect the updated topology of database cluster 330. Forexample, orchestrator 310 may modify the labels in consistent store 320as follows: label demoted source node 331 as “not available,” labelpromoted source node 332 a (i.e., previously replica node 332 a) as“source,” and label replica node 332 b as “replica.” Orchestrator 310may also update the last seen time in consistent store 320 at this time.In some embodiments, orchestrator 310 may update the domain name system(DNS) of promoted source node 332 a and record this in consistent store320 to let user device 350 know that the Internet protocol (IP) of thesource node it may connect to has changed.

At step 470, consistent store 320 may send a notification to user device350 to update its log of the topology of database cluster 330 based onthe update received from orchestrator 310. Consistent store 320 maydetermine whether user device 350 has updated its log of the databasecluster 330 topology based on the most recent update. If thedetermination shows that user device 350 has not yet updated its log ofthe database cluster 330 topology after a specific time interval,consistent store 320 may send another notification instructing userdevice 350 once again to update its log of the database cluster 330topology. Before, during, or after receiving the confirmation from userdevice 350, method 400 may proceed to step 480, where orchestrator 310may terminate the connection between user device 350 and demoted sourcenode 331 and restart the connection between user device 350 and promotedsource node 332 a by executing a “set” command and a “start” command,respectively, in SQL or the like. Orchestrator 310 may also terminatethe connections by, for example, forcing demoted source node 331offline, creating a dynamic KILL statement for each connection, and/oraltering demoted source node 331 to having a single or restricted user.An additional and/or alternative method for updating the log of thetopology on user device 350 is explained in more detail below withreference to FIG. 5.

Similarly, FIG. 4B is a flowchart of an exemplary computerized method405 for replacing replica node 332 a with another replica node followinga failure of replica node 332 a. Method 405 may be performed in 1-10seconds, a substantial improvement from previous solutions. Method 405may be implemented utilizing data stored in any server that must servicea large number of queries such as, for example, SAT system 101, externalfront end system 103, internal front end system 105, transportationsystem 107, SOT system 111, FO system 113, SCM system 117, warehousemanagement system 119, 3rd party fulfillment systems 121A, 121B, and121C, FC Auth 123, and/or LMS 125. Such server may comprise networkedsystems such as those described above in FIG. 3. Method 405 is describedbelow with reference to the networked systems of FIG. 3, but any otherconfiguration of systems, subsystems, or modules may be used to performmethod 405.

At step 415, orchestrator 310 and/or health checker 340 may check theavailability of replica node 332 a. Checking the availability of sourcenode 331 and/or one or more replica nodes 332 a and 332 b may beaccomplished by a detecting a number of failure scenarios, such as afailed source node, a failed source node and failed replica nodes, afailed source node and some failed replica nodes, an unreachable sourcenode, an unreachable source node with lagging replica nodes, not allreplica nodes are replicating the source node data, not all replicanodes are replicating the source node data or have failed, a failedco-source node (should the system have more than one source node), afailed co-source node and failed replica nodes, a failed replica nodewhich itself has replicas, a failed replica node which itself has onereplica which is failing to connect, a failed replica node which itselfhas one replica, a failed replica node which itself has one or morereplicas which have failed, a failed replica node which itself has oneor more replicas—some of which have failed, all replica nodes whichthemselves have one or more replicas have failed or are unable toconnect, an unreachable replica node which itself has one or morereplicas is unreachable, an unreachable replica node which itself hasone or more replicas which are lagging is unreachable.

The failure scenarios may be detected by attempting to reach and/oraccess source node 331 and/or one or more replica nodes 332 a and 332 b,determining one or more replica nodes is failing replication,determining source node 331 and/or one or more replica nodes 332 a and332 b are lagging, and other methods for detecting failure scenarios.

In other embodiments, orchestrator 310 and/or health checker 340 may usesynthetic monitoring to simulate an action or path that a user usinguser device 350 may take on each node in database cluster 330 to checkthe availability of source node 321 and/or one or more replica nodes.The actions or paths may then be continuously monitored at predeterminedintervals to test the availability of each node. Should the actions orpaths be completed successfully, orchestrator 310 and/or health checker340 may determine that the node is available. Further, depending on thescale and the desired availability of the system, the predeterminedintervals could range anywhere from milliseconds to hours. Other methodsfor checking the availability of the nodes include attempting to open aconnection to the nodes, executing a read query against the nodes,executing a non-cached write query against the nodes, executing aprewritten function or procedure that checks for the availability of thenodes, and/or any other method for checking the availability of adatabase.

At step 425, orchestrator 310 and/or health checker 340 may determinewhether replica node 332 a is available from the data collected at step415. Should replica node 332 a be available, method 405 may proceed tostep 427, where orchestrator 310 and/or health checker 340 may update alast seen time in consistent store 320 and wait for a specific intervalof time before checking the availability of replica node 332 a onceagain.

However, if replica node 332 a is not available, method 405 may proceedto step 435, where orchestrator 310 may select a most-updated replicanode from the one or more replica nodes 332, excluding replica node 332a. If health checker 340 determined that replica node 332 a is notavailable, health checker 340 may notify orchestrator 310 that replicanode 332 a is not available, also triggering step 435. The most-updatedreplica node may be, as its name would suggest, the last replica node332 to have been updated with the data from source node 331 before orafter replica node 332 a failed. Orchestrator 310 may store an instanceor list identifying the most-updated replica node and/or may pull datarelating to the most-updated replica node from SAT system 101, externalfront end system 103, internal front end system 105, transportationsystem 107, SOT system 111, FO system 113, SCM system 117, warehousemanagement system 119, 3rd party fulfillment systems 121A, 121B, and121C, FC Auth 123, and/or LMS 125.

At step 445, orchestrator 310 may check to see whether it has selected areplica node 332 before continuing to ensure the failover process iscarried out correctly. Should orchestrator 310 determine that no replicanode 332 has been selected, method 405 may proceed to step 447, whereorchestrator 310 may alert a system administrator (e.g., by sending atext message, email message, push notification, or othermessage/notification), exit method 405, and potentially begin method 405again at step 415 or step 435.

Alternatively, orchestrator 310 may determine that a replica node 332has indeed been selected and method 405 may proceed to step 455. For thepurpose of this illustration, we may assume that the most-updatedreplica node in this case was 332 b. At step 455, orchestrator 310 mayupdate the labels in consistent store 320 to reflect the updatedtopology of database cluster 330. For example, orchestrator 310 maymodify the labels in consistent store 320 as follows: label replica node332 a as “not available,” label source node 331 as “source,” and labelreplica node 332 b as “replica.” Orchestrator 310 may also update thelast seen time in consistent store 320 at this time. In someembodiments, orchestrator 310 may update the domain name system (DNS) ofreplica node 332 b and record this in consistent store 320 to let userdevice 350 know that the Internet protocol (IP) of the replica node itmay connect to has changed.

At step 465, consistent store 320 may send a notification to user device350 to update its log of the topology of database cluster 330 based onthe update received from orchestrator 310. Consistent store 320 maydetermine whether user device 350 has updated its log of the databasecluster 330 topology based on the most recent update. If thedetermination shows that user device 350 has not yet updated its log ofthe database cluster 330 topology after a specific time interval,consistent store 320 may send another notification instructing userdevice 350 once again to update its log of the database cluster 330topology.

Before, during, or after receiving the confirmation from user device350, method 405 may proceed to step 475, where orchestrator 310 mayterminate the connection between user device 350 and replica node 332 aand start a new connection between user device 350 and replica node 332b by executing a “set” command and a “start” command, respectively, inSQL or the like. Orchestrator 310 may also terminate the connections by,for example, forcing source node 331 offline, creating a dynamic KILLstatement for each connection, and/or altering source node 331 to havinga single or restricted user. This step may ensure that user device 350remains connected to a node which serves read commands.

FIG. 5 is a flowchart of an exemplary computerized method 500 forreplacing a connection from user device 350 to database cluster 330after a change in the topology of database cluster 330. Method 500 maybe implemented utilizing data stored in any server that must service alarge number of queries such as, for example, SAT system 101, externalfront end system 103, internal front end system 105, transportationsystem 107, SOT system 111, FO system 113, SCM system 117, warehousemanagement system 119, 3rd party fulfillment systems 121A, 121B, and121C, FC Auth 123, and/or LMS 125. Such server may comprise networkedsystems such as those described above in FIG. 3. Method 500 is describedbelow with reference to the networked systems of FIG. 3, but any otherconfiguration of systems, subsystems, or modules may be used to performmethod 500.

At step 510, user device 350 may monitor consistent store 320 lookingfor any updates which may show a change in the topology of databasecluster 330. If, at step 520, user device 350 determines that there havenot been any updates to consistent store 320, user device 350 may waitfor a predetermined time interval and method 500 may return to step 510.However, if user device 350 determines that consistent store 320 hasbeen updated to reflect a change in the topology of database cluster330, method 500 may proceed to step 530.

At step 530, user device 350 may update the source and replica endpointsidentifying which nodes in database cluster 330 serve which role. Forexample, if consistent store 320 has been updated to label source node331 as “not available,” replica node 332 a as a “source” node, andreplica node 332 b as a “replica” node, then user device 350 will modifyits endpoint data to identify each node consistently with consistentstore 320.

At step 540, user device 350 may use the updated endpoints to replacethe previous connection (e.g., connected to source node 331 to servewrite requests and to replica node 332 a to serve read requests) with anew connection (e.g., connected to replica node 332 a to serve writerequests and to replica node 332 b to serve read requests). Thereplacement may take place automatically or following user input.

Following step 540, user device 350 may perform checks to ensure theconnection replacement was a success. At step 550, if the connection tothe promoted source node (e.g., replica node 332 a) was not successful,user device 350 may attempt to connect to the promoted source node(e.g., replica node 332 a) until the connection is successful. And atstep 560, if the connection to the replica node (e.g., replica node 332b) was not successful, user device 350 may connect to the promotedsource node (e.g., replica node 332 a) instead and allow it to serveboth write and read requests. At step 570, user device 350 may notifyconsistent store 350 of the successful update and supply consistentstore 350 with device statistics.

FIG. 6 is a flowchart of an exemplary computerized method 600 forensuring the database topology is consistent with consistent store 320,and by extension, user device 350. Method 600 may be implementedutilizing data stored in any server that must service a large number ofqueries such as, for example, SAT System 101, SOT system 111, and/or FOsystem 113. Such server may comprise networked systems such as thosedescribed above in FIG. 3. Method 600 is described below with referenceto the networked systems of FIG. 3, but any other configuration ofsystems, subsystems, or modules may be used to perform method 600.

At step 610, health checker 340 may determine the current topology ofdatabase cluster 330 by checking the role of each node in databasecluster 330.

At step 620, health checker 340 may check the topology of databasecluster 330 against the labeling in consistent store 320 to determinewhether the labeling in consistent store 320 is up-to-date andconsistent with the database topology.

At step 630, if the determination is that the labeling and the topologyare consistent, health checker 340 may wait for a predetermined timeinterval and method 600 may return to step 610. However, if the labelingand the topology are not consistent, i.e., at least one node isincorrectly labeled, method 600 may proceed to step 640, where healthchecker 340 may update consistent store 320 to reflect the currenttopology of database cluster 330. The aforementioned may happen, forexample, if there is an error between orchestrator 310 switching therole of one or more nodes in database cluster 330 and updatingconsistent store 320 with the new labels.

At step 650, consistent store 320 sends a notification to user device350 to update its log of the topology of database cluster 330 based onthe update received from health checker 340. Consistent store 320 maydetermine whether user device 350 has updated its log of the databasecluster 330 topology based on the most recent update. If thedetermination shows that user device 350 has not yet updated its log ofthe database cluster 330 topology after a specific time interval,consistent store 320 may send another notification instructing userdevice 350 once again to update its log of the database cluster 330topology. At the same time, before, or after receiving the confirmationfrom user device 350, method 600 may proceed to step 660, whereorchestrator 480 may terminate a connection between user device 350 anda failed node (i.e., a demoted source node 331 or a failed replica node332 a or 332 b) and restart a connection between user device 350 and anappropriate node, as determined by the database topology in consistentstore 320, by executing a “set” command and a “start” command,respectively, in SQL or the like. Orchestrator 310 may also terminatethe connection by, for example, forcing source node 331 offline,creating a dynamic KILL statement for each connection, and/or alteringsource node 331 to having a single or restricted user.

While the present disclosure has been shown and described with referenceto particular embodiments thereof, it will be understood that thepresent disclosure can be practiced, without modification, in otherenvironments. The foregoing description has been presented for purposesof illustration. It is not exhaustive and is not limited to the preciseforms or embodiments disclosed. Modifications and adaptations will beapparent to those skilled in the art from consideration of thespecification and practice of the disclosed embodiments. Additionally,although aspects of the disclosed embodiments are described as beingstored in memory, one skilled in the art will appreciate that theseaspects can also be stored on other types of computer readable media,such as secondary storage devices, for example, hard disks or CD ROM, orother forms of RAM or ROM, USB media, DVD, Blu-ray, or other opticaldrive media.

Computer programs based on the written description and disclosed methodsare within the skill of an experienced developer. Various programs orprogram modules can be created using any of the techniques known to oneskilled in the art or can be designed in connection with existingsoftware. For example, program sections or program modules can bedesigned in or by means of .Net Framework, .Net Compact Framework (andrelated languages, such as Visual Basic, C, etc.), Java, C++,Objective-C, HTML, HTML/AJAX combinations, XML, or HTML with includedJava applets.

Moreover, while illustrative embodiments have been described herein, thescope of any and all embodiments having equivalent elements,modifications, omissions, combinations (e.g., of aspects across variousembodiments), adaptations and/or alterations as would be appreciated bythose skilled in the art based on the present disclosure. Thelimitations in the claims are to be interpreted broadly based on thelanguage employed in the claims and not limited to examples described inthe present specification or during the prosecution of the application.The examples are to be construed as non-exclusive. Furthermore, thesteps of the disclosed methods may be modified in any manner, includingby reordering steps and/or inserting or deleting steps. It is intended,therefore, that the specification and examples be considered asillustrative only, with a true scope and spirit being indicated by thefollowing claims and their full scope of equivalents.

1-20. (canceled)
 21. A computer-implemented system for managing adistributed database, the system comprising: a memory storinginstructions; and one or more processors configured to execute theinstructions to: determine that a source node, in a distributed databasecomprising the source node and one or more replica nodes, is notavailable; in response to the determination, convert a replica node intoa promoted source node; send a signal to a user device connected to thedistributed database, the signal including instructions for the userdevice to update a database topology log based on the promoted sourcenode; determine whether the user device has updated the databasetopology log; and upon determining the user device has not updated thedatabase topology log, continue to send the signal to the user deviceuntil the user device has updated the database topology log.
 22. Thesystem of claim 21, wherein the processor is further configured to:determine that the source node is available; update a last seen time ina data store; wait for a specific time interval; and determine whetherthe source node is available.
 23. The system of claim 21, wherein theprocessor is further configured to: determine that no replica node maybe selected for promotion; upon the determination, alert the userdevice.
 24. The system of claim 21, wherein the processor is furtherconfigured to, upon determining the user device has updated the databasetopology log, terminate a previous connection with the user device. 25.The system of claim 21, wherein determining whether the user device hasupdated the database topology log comprises checking a data store for aconfirmation from the user device.
 26. The system of claim 21, whereinthe selected replica node is a most-updated replica node from the one ormore replica nodes.
 27. The system of claim 21, wherein the distributeddatabase exists in a cloud computing environment.
 28. The system ofclaim 21, wherein the signal includes instructions to connect the userdevice to the promoted source node.
 29. The system of claim 21, whereinthe processor is further configured to update a data store to label thesource node as unavailable and the selected replica node as being apromoted source node.
 30. The system of claim 29, wherein the data storeis a distributed data store comprising a last seen time, databasetopology labels, and user device data and statistics.
 31. Acomputer-implemented method for managing a distributed database, themethod comprising: determining that a source node, in a distributeddatabase comprising the source node and one or more replica nodes, isnot available; in response to the determination, selecting a replicanode from the one or more replica nodes; converting the selected replicanode into a promoted source node; sending a signal to a user deviceconnected to the distributed database, the signal including instructionsfor the user device to update a database topology log based on thepromoted source node; determining whether the user device has updatedthe database topology log; and upon determining the user device has notupdated the database topology log, continuing to send the signal to theuser device until the user device has updated the database topology log.32. The method of claim 31, further comprising: determining that thesource node is available; updating a last seen time in a data store;waiting for a specific time interval; and determining whether the sourcenode is available.
 33. The method of claim 31, further comprising:determining that no replica node may be selected for promotion; upon thedetermination, alerting the user device.
 34. The method of claim 31,further comprising, upon determining the user device has updated thedatabase topology log, terminating a previous connection with the userdevice.
 35. The method of claim 31, wherein determining whether the userdevice has updated the database topology log comprises checking a datastore for a confirmation from the user device.
 36. The method of claim31, wherein the selected replica node is a most-updated replica nodefrom the one or more replica nodes.
 37. The method of claim 31, whereinthe distributed database exists in a cloud computing environment. 38.The method of claim 31, wherein the signal includes instructions toconnect the user device to the promoted source node.
 39. The method ofclaim 31, further comprising updating a data store to label the sourcenode as unavailable and the selected replica node as being a promotedsource node.
 40. The method of claim 39, wherein the data store is adistributed data store comprising a last seen time, database topologylabels, and user device data and statistics.